How to See Likes on Twitter (X) in 2026: What Still Works

X made likes private in June 2024. If you are a founder, marketer, or in sales, you probably noticed. The list of people who liked someone else’s post disappeared overnight.

Here is what still works: you can see every like on your own posts, and X Analytics still exports that data. For other people’s posts, you can only see the total like count, not the individual users. The workarounds below cover both scenarios.

Why X Likes Still Matter, Even When They’re Hidden

Hiding public likes was not just a cosmetic update. It changed how anyone in sales or marketing measures engagement on X. At first it felt like a step backward, especially for anyone using the platform to find warm leads or gauge public sentiment.

But it also forced a useful shift. The data you have about your own audience (who liked, when, and how often) is now your strongest signal. Knowing who interacts with your content is the first step in identifying engaged prospects. We cover the same idea for LinkedIn in our guide on what impressions mean and how to use them.

This flowchart gives you a quick visual breakdown of what’s possible today.

As you can see, your access to like data now almost entirely depends on whether you’re the author of the post. This really hammers home the importance of tracking your own content’s performance.

What Changed in June 2024

Twitter launched in 2006, and for eighteen years seeing who liked a tweet was public. In June 2024, the platform made its privacy-focused shift and the per-user like list disappeared from other people’s posts.

The reaction was immediate. Google Trends data from mid-2024 showed a 35% spike in searches for third-party analytics tools in the weeks that followed. For B2B founders and sales teams who relied on those social signals, it made clear how much they depended on public engagement data.

Here is a summary of your options as of mid-2026.

Your Options for Viewing X (Twitter) Likes in 2026

Method	Who Can Use It	What You Can See
Viewing Your Own Likes	Anyone	A complete list of every user who liked your posts.
Viewing Another User’s Likes	No one (publicly)	You can only see a total like count, not the list of users.
Using Your “Likes” Tab	You	A private list of all the posts you have personally liked.
Third-Party Tools	Users with API access	Limited data; these tools can no longer pull public like lists from others.

The focus has shifted inward. The data you can access about your own audience is now your most powerful asset.

Stop worrying about the competitor engagement data you lost. The people liking your posts are your most valuable audience. They are your warm leads, your biggest fans, and the key to refining your content strategy. If you want to increase that engagement in the first place, our guide on how to get likes on tweets covers ten tactics that work in 2026.

Using X Analytics to See Your Own Post Likes

Even with all the recent changes on X, your own performance data is still right where you left it. In fact, getting comfortable with your X Analytics dashboard is more important than ever for figuring out what’s actually working. It’s the most reliable way to see the likes on your own content.

Getting there is simple. Just head to your profile, click the three-dot menu, and then select Analytics. You’ll find a breakdown of all your key metrics here - impressions, engagement rates, and of course, the number of likes for every single post.

Go Beyond the Dashboard with a Data Export

Looking at individual tweet performance is helpful, but the real insights come when you look at the big picture. This is where exporting your data comes in handy. The analytics dashboard lets you download all your tweet activity as a simple CSV file.

Once you open that file in a spreadsheet program, you can start asking some powerful questions:

• What happens if you sort the entire list by the ‘likes’ column? You’ll instantly see your all-time greatest hits.
• Can you spot any trends? Filter the data to a specific month or quarter to see how performance has changed over time.
• Are there any posts with a ton of likes but surprisingly low impressions? That’s a great sign that you’ve created something that deeply resonates with a specific niche.

For instance, I once worked with a B2B SaaS founder who exported her last quarter’s data. She quickly discovered that short video demos earned 3x more likes than any of her posts with static images. That one piece of information completely reshaped her content plan for the rest of the year.

My Advice: Don’t just count your likes - figure out what they mean. When you export your data, you can start spotting the patterns in your best-performing content. This stops being about vanity metrics and starts being about finding the exact topics and formats your audience wants more of.

This is how you move from guessing what might work to knowing what does work. You get solid proof, allowing you to confidently double down on the content that will build a genuinely engaged audience on X.

How to See What Another User Engages With

Since the 2024 privacy update on X, you can no longer see the list of users who liked someone else’s tweet. That direct window is closed.

You can still piece together a user’s interests by looking at their other public interactions: replies, reposts, and quotes. It is less about direct like data and more about mapping out their engagement footprint through what remains public.

This kind of intelligence work is incredibly valuable. After all, with a median engagement rate across all industries sitting at a tiny 0.046%, every public interaction - a like, reply, or repost - is a significant signal of interest. If you want to dive deeper into how data access has evolved on the platform, you can read these insights on historical Twitter data.

Use Advanced Search to Uncover Engagement Clues

Your best friend for this kind of detective work is X’s own Advanced Search. It’s a surprisingly powerful tool that lets you find tweets a specific user has replied to or mentioned, which almost always correlates with what they’re liking.

Think of it this way: if a prospect is constantly replying to posts about “AI in marketing,” you can bet they’re liking those posts, too. Advanced Search helps you map that public conversation history.

Here are a few search combinations I use all the time:

• to:[username]: Pinpoints every reply a user has sent to a specific account. This is great for seeing who they’re talking to.
• from:[username]: The basic filter, showing all tweets from a particular person.
• "keyword" (from:[username]): This is where it gets interesting. It finds tweets from a user that contain a specific word or phrase.

By layering these operators, you can build a surprisingly detailed picture of someone’s professional interests. For example, a search like "sales automation" (to:HubSpot) (from:Prospect_Handle) would instantly show you if your prospect is talking about sales automation with a major player like HubSpot. That’s a powerful intent signal you can act on.

Using Third-Party Tools to Uncover Hidden Like Data

While X keeps other users’ individual like lists private, third-party tools can still surface useful engagement data at the aggregate level. They cannot show you exactly who liked a specific tweet (that API endpoint is restricted), but they can show you which users are replying, reposting, and quoting content around a topic.

Platforms like BrandMentions, Tweet Binder, and Minter.io are built for this kind of monitoring. They work best for tracking which accounts consistently engage with a topic or keyword, not for pulling a specific like list.

Unlocking Historical Engagement Data

With hundreds of billions of posts circulating on X, narrowing down engagement signals takes tooling. BrandMentions can pull mention and engagement data going back over 10 years, giving you aggregate metrics like total likes on posts tied to a specific keyword or event.

Tweet Binder is another useful option. Its free 7-day reports show the “most liked” tweets on a topic and which accounts are driving the conversation. Paid plans unlock up to 35,000 tweets dating back to 2006. For B2B founders looking for an edge, this kind of topic-level intelligence can surface patterns worth acting on.

While you cannot see the individual like list on another user’s post, you can use third-party analytics to see which accounts consistently engage around certain topics. That aggregate signal is a useful proxy for identifying potential leads.

From Data Points to Strategic Action

But these tools aren’t just for passively watching brand mentions - they’re active lead generation engines. You can use them to build a list of influential accounts that consistently engage with your industry’s keywords. Knowing who these people are helps you focus your outreach where it counts.

Many of these platforms offer features that provide the same kind of signal-based intelligence found in dedicated lead-gen tools. If you are looking to automate how you find and engage prospects, our comparison of Embers and PhantomBuster covers the key differences.

Ultimately, the goal is to build a repeatable system that turns simple engagement data into real conversations.

Turning Engagement Signals into Sales Opportunities

Now that you know how to find likes on X, the value comes when you start turning those engagements into conversations and warm leads. This is where social selling on X becomes useful.

The goal is to spot prospects who are consistently engaging with your content. A single like is a nod. A pattern of likes is an intent signal.

For instance, if a marketing director at one of your target accounts likes three of your posts about AI in marketing this week, they’re not just scrolling. They’re actively researching and interested.

Crafting a Non-Intrusive Outreach Message

Once you have spotted a promising prospect, the key is to be helpful, not pushy. A generic cold pitch gets ignored. Their engagement gives you a natural reason to start a conversation.

Here’s a simple, effective way to frame your outreach:

• The Warm Opener: “Hey [Name], I noticed you liked our post on the latest challenges in marketing attribution.”
• Adding Real Value: “It’s a tough nut to crack. We actually put together a quick guide on how our clients are handling it. Thought it might be useful for you.”
• The Open-Ended Question: “Are you running into any of those same headaches on your end?”

This approach shows you are paying attention to their interests, not spamming a list. It changes the dynamic from a cold interruption to a relevant touchpoint.

If you are serious about this, using a dedicated social selling platform can help you organize and scale these efforts without losing that personal touch.

Build a repeatable process that turns passive “likers” into active prospects. By using their own engagement as the reason you are reaching out, you create a connection that feels authentic and immediately relevant.

Frequently Asked Questions About X Likes

A few common questions about how X handles likes in 2026.

Can I See Who Liked a Tweet That Is Not Mine?

No. Since the June 2024 privacy update, only the author of a post can see the full list of who liked it. Everyone else can see the total like count, but the specific list of users is private to the creator.

Why Did X Hide Public Like Counts?

X framed the move as a way to boost user privacy and encourage more authentic engagement. Hiding public likes reduces the social pressure to “like” what is already popular. The idea is that users interact with content they genuinely find valuable rather than following the crowd.

By making likes private to the author, the platform shifted the focus from a post’s popularity score to the substance of the content itself.

Are There Any Free Tools to See Historical X Likes?

Most free tools are limited. Tweet Binder offers a free tier, but it is restricted to the last seven days of data and a small sample of posts.

If you need comprehensive historical data (tracking engagement on a topic over months or analyzing user patterns across quarters) a paid subscription to a professional-grade analytics tool is usually required.